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Related Questions
- Can you explain the concept of noise in the context of machine learning and human-in-the-loop approaches?
- How do you identify and remove noisy labels in human-labeled datasets to improve model performance?
- What are some common pitfalls to avoid when collecting negative examples through human-in-the-loop approaches?
- Can you discuss the importance of data quality and how it affects the performance of machine learning models?
- What strategies can be used to improve the quality of human-labeled data in machine learning applications?
- How do you handle the issue of annotation drift in human-labeled datasets, where the quality of labels degrades over time?
- Can you describe a method for evaluating the reliability of human-labeled data in machine learning models?
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